The increased demand for data enterprise and other storage solutions has fueled corresponding demand in data backup and management tools. Companies, government and scientific organizations and others may require the reliable backup of gigabytes or terabytes of data, or more for archival and other purposes. While physical storage media such as storage area networks, optical storage media, redundant arrays of inexpensive disk (RAID) and other platforms have increased the total archival capacity available to data managers, the ability to efficiently harvest large data backups to host facilities has not always similarly progressed.
For instance, a network administrator may periodically wish to extract the data updates stored to network storage, such as server drives on a local area network (LAN), and transport that data to a secure backup repository at a remote site. However, scheduling and executing that type of large-scale data transport is not always efficient using current technology. For instance, in the case of storing LAN data to a remote site, the administrator may attempt to move that quantity of data using a conventional network protocol, such as the Transfer Control Protocol (TCP).
However, TCP as one transport solution may prove to be a difficult vehicle to communicate the data backup to the remote host, in part because TCP tends to decompose data into comparatively small packets, on the order of a few tens of bytes to a few thousands of bytes. When attempting to drive gigabytes of original or update data to a remote host, that scale will not suffice for efficient transport. Moreover, when performing data flow control on the channel, TCP may pause to seek available bandwidth or capacity on the channel as small as a few thousand bytes, stop and fill that available space in the pipe, and then wait for additional open slots. Again, pushing data on the order of megabytes, gigabytes or more through an intermittent channel at those scales is not efficient when using the granularity of TCP API. Better large-scale and other data backup technologies are desirable. Other problems exist.